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Ying Guo 0004
Person information
- affiliation: North China University of Technology, Beijing, China
- affiliation (PhD 2019): Shanghai Jiao Tong University, School of Electronic Information and Electrical Engineering, Shanghai, China
Other persons with the same name
- Ying Guo — disambiguation page
- Ying Guo 0001
— Commonwealth Scientific and Industrial Research Organization, Marsfield, NSW, Australia
- Ying Guo 0002
- Ying Guo 0003
- Ying Guo 0005
- Ying Guo 0006
- Ying Guo 0007 — Qingdao University of Science and Technology, College of Information Science and Technology, Qingdao, China (and 1 more)
- Ying Guo 0008
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2020 – today
- 2024
- [j12]Yongkang Jiang
BenchMFC: A benchmark dataset for trustworthy malware family classification under concept drift. Comput. Secur. 139: 103706 (2024) - [j11]Yongkang Jiang
Crowdsourcing Malware Family Annotation: Joint Class-Determined Tag Extraction and Weakly-Tagged Sample Inference. IEEE Trans. Netw. Serv. Manag. 21(4): 4763-4776 (2024) - 2023
- [j10]Chong Di
Learning automata-accelerated greedy algorithms for stochastic submodular maximization. Knowl. Based Syst. 282: 111118 (2023) - 2022
- [j9]Ying Guo, Chong Di, Shenghong Li:
A novel reduced parameter s-model of estimator learning automata in the switching non-stationary environment. Neural Comput. Appl. 34(9): 6811-6824 (2022) - [j8]Ying Guo, Shenghong Li:
A multi-Markovian switching-based strategy for solving the stochastic point location problem. Neural Comput. Appl. 34(9): 6825-6846 (2022) - 2020
- [j7]Haonan Guo
Learning Automata Based Competition Scheme to Train Deep Neural Networks. IEEE Trans. Emerg. Top. Comput. Intell. 4(2): 151-158 (2020)
2010 – 2019
- 2019
- [j6]Chong Di
Learning Automata-Based Access Class Barring Scheme for Massive Random Access in Machine-to-Machine Communications. IEEE Internet Things J. 6(4): 6007-6017 (2019) - [j5]Ying Guo
A Non-Monte-Carlo Parameter-Free Learning Automata Scheme Based on Two Categories of Statistics. IEEE Trans. Cybern. 49(12): 4153-4166 (2019) - 2017
- [j4]Ying Guo, Hao Ge, Shenghong Li:
A set of novel continuous action-set reinforcement learning automata models to optimize continuous functions. Appl. Intell. 46(4): 845-864 (2017) - [j3]Ying Guo, Hao Ge, Shenghong Li:
A loss function based parameterless learning automaton scheme. Neurocomputing 260: 331-340 (2017) - [j2]Ying Guo, Shenghong Li, Wen Jiang, Bo Zhang, Yinghua Ma:
Learning automata-based algorithms for solving the stochastic shortest path routing problems in 5G wireless communication. Phys. Commun. 25: 376-385 (2017) - 2016
- [j1]Hao Ge, Yifan Wang, Shenghong Li, Chun Lung Philip Chen
A cooperative framework of learning automata and its application in tutorial-like system. Neurocomputing 188: 311-318 (2016) - [c3]Jinchao Huang, Yan Yan, Ying Guo, Shenghong Li:
A New Scheme Based on HSSL for Solving the Stochastic Point Location Problem. DSC 2016: 209-214 - [c2]Ying Guo, Hao Ge, Jinchao Huang, Shenghong Li:
A General Strategy for Solving the Stochastic Point Location Problem by Utilizing the Correlation of Three Adjacent Nodes. DSC 2016: 215-221 - [c1]Xiaochun Li, Fangqi Li, Ying Guo, Jinchao Huang:
Gaussian Iteration: A Novel Way to Collaborative Filtering. ICIC (3) 2016: 260-270
Coauthor Index
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